The next step Wireless Sensor Networks More than … · The next step – Wireless Sensor Networks More than sources of data ... •Core module with controller, ... 2. Coupled Training

1

SN

GW SN

SN

SN SN

SN SN

SN

SN SN

SN

GW

GW

GW

Bluetooth

SN

Univ.-Prof. Dr.-Ing. Jochen H. Schiller http://cst.mi.fu-berlin.de RFID – 110913

The next step – Wireless Sensor Networks More than sources of data…

Jochen H. Schiller

Computer Systems & Telematics

Freie Universität Berlin

[email protected]

2

Characteristics of RFID/sensor nodes

• (passive) RFID

• Transmission of ID as soon as external power available

• Very simple computations possible

• Active RFID

• Internal energy source or energy harvesting

• Longer range, more computing power

• Wireless Sensor Nodes

• One or more sensors attached

• Preprocessing of data

• Simple operating systems

• But typically used as sources of data, forwarding data to a sink, external computation of events


3 Univ.-Prof. Dr.-Ing. Jochen H. Schiller http://cst.mi.fu-berlin.de RFID – 110913

Sensor networks: the “standard” (?) applications (since >10 years)

Inject sensors in

the human body ;-)

Discover disasters early

Gather information about

unknown area

Detect leakages

Detect structural

damage


Typical properties of wireless sensor networks

• Sensor nodes (SN) monitor and control the environment

• Nodes process data and forward data via radio

• Integration into the environment, typically attached to other networks over a gateway (GW)

• Network is self-organizing and energy efficient

• Potentially high number of nodes at very low cost per node

SN

GW

SN

SN

SN SN

SN SN

SN

SN SN

SN

GW

GW

GW

LTE, TETRA, …

SN


Promising applications for WSNs

• Machine and vehicle monitoring • Sensor nodes in moveable parts • Monitoring of hub temperatures, fluid levels …

• Intelligent buildings, building monitoring • Intrusion detection, mechanical stress detection • Precision HVAC with individual climate

• Environmental monitoring, person tracking • Monitoring of wildlife and national parks • Cheap and (almost) invisible person monitoring • Monitoring waste dumps, demilitarized zones

• Health & medicine

• Long-term monitoring of patients with minimal restrictions • Intensive care with relative great freedom of movement

• … and many more: logistics (total asset management, RFID), telematics … • WSNs are quite often complimentary to fixed networks!


Robust HW needed - example: ScatterWeb’s Modular Sensor Board

• Modular design

• Core module with controller, transceiver, SD-card slot

• Charging/programming/GPS/GPRS module

• Sensor carrier module

• Software

• Firmware (C interface)

• TinyOS, Contiki, µkleos …

• Routing, management, flashing …

• ns-2 simulation models

• Integration into Visual Studio, Eclipse, LabVIEW, Robotics Studio …

• Sensors attached on demand

• Acceleration, humidity, temperature, luminosity, noise detection, vibration, PIR movement detection…

7

Distributed Embedded System Testbed

• Hybrid wireless multi-transceiver testbed for long-term studies

• Consists of a wireless mesh network (WMN) and a wireless sensor network (WSN)

• Wireless mesh routers equipped with 802.11a/b/g network adapters and wireless sensor nodes

• www.des-testbed.net


http://www.des-testbed.net/





Example Application: Temperature Measurement in the Baltic Sea

Baltic Sea

Temperature

Sensors

…

…

Sensor Network

GPRS wireless connection

Radio Radio Buoy with Sensors

Weight/

Anchor

Ground


Making WSNs seawater-proof

Protection of nodes in oil (incl. antenna)

Chain of Sensors


Robustness – the real Challenge of WSNs

• WSNs have to work – as simple as this sound as complicated it is to achieve!

• Example: Alpine WSN

• ScatterWeb nodes collect temperature data from various sensor

• GPRS at gateway


Monitoring Rocks in the Swiss Alps


Experiment: Fence Protections

ALARM!

ALARM!

ALARM!


Sensor Integration


Event Detection

Different Types of Events (Raw Data)

0

100

200

300

400

500

600

700

800

900

1000

90.00 100.00 110.00 120.00 130.00 140.00 150.00 160.00 170.00 180.00 190.00

Time (s)

Inte

ns

ity

Kicking

Shaking

Climbing Peeking

Leaning

Time (s)

Inte

nsity


Challenging application: safety for rescue forces


Monitoring of vital parameters

Berliner Feuerwehr


Localization on the disaster site


Project FeuerWhere – the extreme challenge

TETRA Mobile, self-organizing WSN

TETRA trunked radio network

Data transmission & localization

Berliner Feuerwehr 4450 fire fighters 300000 incidents/year (8000 fires)


Example Application: Habitat Monitoring/Skomer Island UK

Manx Shearwater


Combination of RFID and ScatterWeb

• Main challenge: robustness, reliability, easy-to-use

• Joint project with Oxford University and MSRC

http://skomerisland.codeplex.com/

http://skomerisland.codeplex.com/


Orwell for birds – total monitoring

22

Next step: AvianGPS Cooperative monitoring

• Core: MSP430F1610 + CC1101 • Sensors: GPS, Pressure Sensor, Light Sensor

• Weight: 7 g (without battery) • Size: 24 mm x 45 mm

• Partners: Freie Universität Berlin, University of Oxford,

Microsoft Research Ltd.


23

Lightweight sensor module…


24

…attached to the bird


25

Tracking the flock of birds


26

Beyond being simple data sources: Distibuted Event Detection

• In-network data processing is a key feature of Wireless Sensor Networks (WSNs) • Reduce communication with base station • Extend network lifetime

• Example: Distributed, in-network event detection • Decide locally, within the neighborhood, whether an event

occurred • Send only confirmed events to the base station, not raw data

Passive/active Node

Data Traffic

Event

Base Station

Radio Link


27

Applications of distributed event detection

1. Fence Monitoring AVS-Extrem 2. Coupled Training Device


28

1. Sensor Node Platform

• Energy awareness

• Communication issues

• Sensor (acceleration)

• Flexibility

2. Housing

• Look & feel and usability

• Thin housing

• Integration of PCB-Shape & energy supply

3. Event Detection

• Decentralized pattern recognition

• No dedicated infrastructure

Design Challenges

Feature Extraction

node n-1 node n node n+1

Preprocessing

Classification

Feature Distribution

Event Report


31

Distributed Event Detection – How it works

1. Supervised Training • Expose sensor network to series of training events • Extract ALL features and transmit to control station

2. Setup • Select best subset of features, calculate prototype vector for each event • Configure nodes to only extract/transmit selected features

3. Event Detection with Feedback • Calculate & exchange features to neighbors, fuse own & received vectors to

complete fingerprint • Evaluate events with Euclidian-distance based prototype classifier


3. Event Detection with Feedback

Feedback Trainee Wireless Sensor Network Supervisor Trainee Wireless Sensor Network Control Station

2. Setup 1. Supervised Training

Calculation & Upload of Prototype Vectors

Extract Features

Exchange & Fuse Features

Classification of Events

Transmit Features

32

Distributed Event Detection in Detail

1. Preprocessing:

• Sample raw data

• Filter and smoothen data

2. Feature Extraction:

• Extract application-specific set of features from raw data

• Selection of appropriate features is part of training (cross-validation)

3. Feature Distribution:

• Send features to neighborhood

• Retransmit features in case of transmission failures

4. Classification:

• Fuse received and own features to feature vector

• Classify feature vector (prototype classifier)

• Report to base station, if event is configured as relevant

5. Report:

• Possible alarm or event feedback

Feature Extraction

node n-1 node n node n+1

Preprocessing

Classification

Feature Distribution

Event Report

Fence Monitoring Movement Detection


35

Possible wireless & motion-based applications

4. Rehabilitation

Supervision Training

Future Work

Autonomous Training

1. Fence Monitoring AVS-Extrem

Done

2. Coupled Training Device

Done

3. Decoupled Training Device

Work in Progress


36

Bridge monitoring

GSM-Modul 1. Deployment Technical Initialization

Event-Feedback via GSM-Modul

868 MHz

2. Surveillance with Feedback

Collection + Exchange of data

Exchange of data Classification

868 MHz

Upload of Reference Data


37

Conclusion

• WSNs go beyond being simply data sources

• In-network processing

• Saves energy

• Increases reliability of system and results

• Lowers overall costs

• Robustness of the systems is still a challenge

• Simple and cheap nodes must survive in rough environments

• Interesting future applications

• Integration into logistics

• Did all parts stay together, have the same movement pattern?

• Integration into construction machines

• Pay-per-usage, overstress monitoring

• …


Documents

The next step Wireless Sensor Networks More than … · The next step – Wireless Sensor Networks More than sources of data ... •Core module with controller, ... 2. Coupled Training